Yuanhua Huang

CamoTSS identifies and quantifies alternative transcription start sites from 5' scRNA-seq data, revealing regulatory patterns in human cell types and diseases.

LocusMasterTE improves TE expression quantification by integrating long-read and short-read RNA-seq data using an EM algorithm.

This paper develops MTtrans, a multi-task learning model that identifies robust, generalizable cis-regulatory motifs in 5' UTRs by integrating diverse datasets, showing improved accuracy and cross-species transferability.

UniTVelo improves RNA velocity modeling by incorporating temporal regularization, enhancing trajectory inference across diverse biological systems.

The paper defines the single-cell spatiotemporal gene expression landscape of human embryonic development using stem-cell-derived organoids and identifies key developmental signatures and signaling pathways.

SpatialDM identifies spatially co-expressed ligand-receptor pairs and communication patterns in spatial transcriptomics data with high accuracy and scalability.

DCATS performs differential composition analysis for complex single-cell experiments, maintaining high sensitivity and specificity compared to existing methods.

MQuad identifies clonally informative mitochondrial variants from single-cell sequencing data with high sensitivity and specificity, outperforming existing methods.

This paper introduces VeloAE, a method to improve the accuracy and stability of cell transition estimation from RNA velocity data across multiple datasets.

This paper introduces BRIE2, a method to identify splicing phenotypes from single-cell transcriptomic data, showing it can detect differential alternative splicing and improve RNA velocity analysis.

Cellsnp-lite is a fast and memory-efficient tool for genotyping single-cell sequencing data, showing improved performance over existing methods.

The paper predicts RNA splicing kinetics using genomic sequences and RNA binding proteins across single-cell RNA-Seq data from human and mouse tissues.

Vireo is a Bayesian model for demultiplexing pooled single-cell RNA-seq data without requiring genotype references, showing robustness in simulations and real data.

Cardelino integrates whole exomes and single-cell transcriptomes to identify clone-of-origin and reveal phenotypic impacts of somatic variants in human fibroblasts.

This paper introduces BRIE, a Bayesian model for accurate splicing quantification in single-cell RNA-seq, enabling differential isoform analysis between datasets.